{
 "nbformat": 4,
 "nbformat_minor": 0,
 "metadata": {
  "accelerator": "TPU",
  "colab": {
   "name": "Keras MNIST TPU end-to-end - training, saved model and online inference",
   "provenance": [],
   "collapsed_sections": []
  },
  "environment": {
   "name": "tf22-cpu.2-2.m47",
   "type": "gcloud",
   "uri": "gcr.io/deeplearning-platform-release/tf22-cpu.2-2:m47"
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "xqLjB2cy5S7m"
   },
   "source": [
    "## MNIST on TPU (Tensor Processing Unit)<br>or GPU using tf.Keras and tf.data.Dataset\n",
    "<table><tr><td><img valign=\"middle\" src=\"https://raw.githubusercontent.com/GoogleCloudPlatform/tensorflow-without-a-phd/master/tensorflow-rl-pong/images/keras-tensorflow-tpu300px.png\"   width=\"300\" alt=\"Keras+Tensorflow+Cloud TPU\"></td></tr></table>\n",
    "\n",
    "\n",
    "This sample trains an \"MNIST\" handwritten digit \n",
    "recognition model on a GPU or TPU backend using a Keras\n",
    "model. Data are handled using the tf.data.Datset API. This is\n",
    "a very simple sample provided for educational purposes. Do\n",
    "not expect outstanding TPU performance on a dataset as\n",
    "small as MNIST.\n",
    "\n",
    "<h3><a href=\"https://cloud.google.com/gpu/\"><img valign=\"middle\" src=\"https://raw.githubusercontent.com/GoogleCloudPlatform/tensorflow-without-a-phd/master/tensorflow-rl-pong/images/gpu-hexagon.png\" width=\"50\"></a>  &nbsp;&nbsp;Train on GPU or TPU&nbsp;&nbsp; <a href=\"https://cloud.google.com/tpu/\"><img valign=\"middle\" src=\"https://raw.githubusercontent.com/GoogleCloudPlatform/tensorflow-without-a-phd/master/tensorflow-rl-pong/images/tpu-hexagon.png\" width=\"50\"></a></h3>\n",
    "\n",
    "  1. Select a GPU or TPU backend (Runtime > Change runtime type) \n",
    "  1. Run all cells up to and including \"Train and validate the model\" and \"Visualize predictions\".\n",
    "\n",
    "<h3><a href=\"https://cloud.google.com/ml-engine/\"><img valign=\"middle\" src=\"https://raw.githubusercontent.com/GoogleCloudPlatform/tensorflow-without-a-phd/master/tensorflow-rl-pong/images/mlengine-hexagon.png\" width=\"50\"></a>  &nbsp;&nbsp;Deploy to AI Platform</h3>\n",
    "\n",
    "  1. Configure a Google cloud project and bucket as well as the desired model name in \"Deploy the trained model\".\n",
    "  1. Run the remaining cells to the end to deploy your model to Cloud AI Platform Prediction and test the deployment.\n",
    "\n",
    "TPUs are located in Google Cloud, for optimal performance, they read data directly from Google Cloud Storage (GCS)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "qpiJj8ym0v0-"
   },
   "source": [
    "### Imports"
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "AoilhmYe1b5t",
    "outputId": "b2d4749c-2c04-4306-bc3d-8c307fd282c0"
   },
   "source": [
    "import os, re, time, json\n",
    "import PIL.Image, PIL.ImageFont, PIL.ImageDraw\n",
    "import numpy as np\n",
    "import tensorflow as tf\n",
    "from matplotlib import pyplot as plt\n",
    "AUTOTUNE = tf.data.AUTOTUNE\n",
    "print(\"Tensorflow version \" + tf.__version__)"
   ],
   "execution_count": 1,
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "Tensorflow version 2.6.0\n"
     ]
    }
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "cellView": "form",
    "id": "qhdz68Xm3Z4Z"
   },
   "source": [
    "#@title visualization utilities [RUN ME]\n",
    "\"\"\"\n",
    "This cell contains helper functions used for visualization\n",
    "and downloads only. You can skip reading it. There is very\n",
    "little useful Keras/Tensorflow code here.\n",
    "\"\"\"\n",
    "\n",
    "# Matplotlib config\n",
    "plt.rc('image', cmap='gray_r')\n",
    "plt.rc('grid', linewidth=0)\n",
    "plt.rc('xtick', top=False, bottom=False, labelsize='large')\n",
    "plt.rc('ytick', left=False, right=False, labelsize='large')\n",
    "plt.rc('axes', facecolor='F8F8F8', titlesize=\"large\", edgecolor='white')\n",
    "plt.rc('text', color='a8151a')\n",
    "plt.rc('figure', facecolor='F0F0F0')# Matplotlib fonts\n",
    "MATPLOTLIB_FONT_DIR = os.path.join(os.path.dirname(plt.__file__), \"mpl-data/fonts/ttf\")\n",
    "\n",
    "# pull a batch from the datasets. This code is not very nice, it gets much better in eager mode (TODO)\n",
    "def dataset_to_numpy_util(training_dataset, validation_dataset, N):\n",
    "  \n",
    "  # get one batch from each: 10000 validation digits, N training digits\n",
    "  batch_train_ds = training_dataset.unbatch().batch(N)\n",
    "  \n",
    "  # eager execution: loop through datasets normally\n",
    "  for validation_digits, validation_labels in validation_dataset:\n",
    "    validation_digits = validation_digits.numpy()\n",
    "    validation_labels = validation_labels.numpy()\n",
    "    break\n",
    "  for training_digits, training_labels in batch_train_ds:\n",
    "    training_digits = training_digits.numpy()\n",
    "    training_labels = training_labels.numpy()\n",
    "    break\n",
    "  \n",
    "  # these were one-hot encoded in the dataset\n",
    "  validation_labels = np.argmax(validation_labels, axis=1)\n",
    "  training_labels = np.argmax(training_labels, axis=1)\n",
    "  \n",
    "  return (training_digits, training_labels,\n",
    "          validation_digits, validation_labels)\n",
    "\n",
    "# create digits from local fonts for testing\n",
    "def create_digits_from_local_fonts(n):\n",
    "  font_labels = []\n",
    "  img = PIL.Image.new('LA', (28*n, 28), color = (0,255)) # format 'LA': black in channel 0, alpha in channel 1\n",
    "  font1 = PIL.ImageFont.truetype(os.path.join(MATPLOTLIB_FONT_DIR, 'DejaVuSansMono-Oblique.ttf'), 25)\n",
    "  font2 = PIL.ImageFont.truetype(os.path.join(MATPLOTLIB_FONT_DIR, 'STIXGeneral.ttf'), 25)\n",
    "  d = PIL.ImageDraw.Draw(img)\n",
    "  for i in range(n):\n",
    "    font_labels.append(i%10)\n",
    "    d.text((7+i*28,0 if i<10 else -4), str(i%10), fill=(255,255), font=font1 if i<10 else font2)\n",
    "  font_digits = np.array(img.getdata(), np.float32)[:,0] / 255.0 # black in channel 0, alpha in channel 1 (discarded)\n",
    "  font_digits = np.reshape(np.stack(np.split(np.reshape(font_digits, [28, 28*n]), n, axis=1), axis=0), [n, 28*28])\n",
    "  return font_digits, font_labels\n",
    "\n",
    "# utility to display a row of digits with their predictions\n",
    "def display_digits(digits, predictions, labels, title, n):\n",
    "  plt.figure(figsize=(13,3))\n",
    "  digits = np.reshape(digits, [n, 28, 28])\n",
    "  digits = np.swapaxes(digits, 0, 1)\n",
    "  digits = np.reshape(digits, [28, 28*n])\n",
    "  plt.yticks([])\n",
    "  plt.xticks([28*x+14 for x in range(n)], predictions)\n",
    "  for i,t in enumerate(plt.gca().xaxis.get_ticklabels()):\n",
    "    if predictions[i] != labels[i]: t.set_color('red') # bad predictions in red\n",
    "  plt.imshow(digits)\n",
    "  plt.grid(None)\n",
    "  plt.title(title)\n",
    "  \n",
    "# utility to display multiple rows of digits, sorted by unrecognized/recognized status\n",
    "def display_top_unrecognized(digits, predictions, labels, n, lines):\n",
    "  idx = np.argsort(predictions==labels) # sort order: unrecognized first\n",
    "  for i in range(lines):\n",
    "    display_digits(digits[idx][i*n:(i+1)*n], predictions[idx][i*n:(i+1)*n], labels[idx][i*n:(i+1)*n],\n",
    "                   \"{} sample validation digits out of {} with bad predictions in red and sorted first\".format(n*lines, len(digits)) if i==0 else \"\", n)\n",
    "    \n",
    "# utility to display training and validation curves\n",
    "def display_training_curves(training, validation, title, subplot):\n",
    "  if subplot%10==1: # set up the subplots on the first call\n",
    "    plt.subplots(figsize=(10,10), facecolor='#F0F0F0')\n",
    "    plt.tight_layout()\n",
    "  ax = plt.subplot(subplot)\n",
    "  ax.grid(linewidth=1, color='white')\n",
    "  ax.plot(training)\n",
    "  ax.plot(validation)\n",
    "  ax.set_title('model '+ title)\n",
    "  ax.set_ylabel(title)\n",
    "  ax.set_xlabel('epoch')\n",
    "  ax.legend(['train', 'valid.'])"
   ],
   "execution_count": 2,
   "outputs": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "VE6zp3q_HNTi"
   },
   "source": [
    "*(you can double-ckick on collapsed cells to view the non-essential code inside)*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "R4jujVYWY9-6"
   },
   "source": [
    "### TPU or GPU detection"
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "id": "Hd5zB1G7Y9-7"
   },
   "source": [
    "try: # detect TPUs\n",
    "    tpu = tf.distribute.cluster_resolver.TPUClusterResolver.connect() # TPU detection\n",
    "    strategy = tf.distribute.TPUStrategy(tpu)\n",
    "except ValueError: # detect GPUs\n",
    "    strategy = tf.distribute.MirroredStrategy() # for GPU or multi-GPU machines\n",
    "    #strategy = tf.distribute.get_strategy() # default strategy that works on CPU and single GPU\n",
    "    #strategy = tf.distribute.experimental.MultiWorkerMirroredStrategy() # for clusters of multi-GPU machines\n",
    "print(\"Number of accelerators: \", strategy.num_replicas_in_sync)"
   ],
   "execution_count": null,
   "outputs": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Lvo0t7XVIkWZ"
   },
   "source": [
    "### Parameters"
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "id": "cCpkS9C_H7Tl"
   },
   "source": [
    "BATCH_SIZE = 64 * strategy.num_replicas_in_sync # Gobal batch size.\n",
    "# The global batch size will be automatically sharded across all\n",
    "# replicas by the tf.data.Dataset API. A single TPU has 8 cores.\n",
    "# The best practice is to scale the batch size by the number of\n",
    "# replicas (cores). The learning rate should be increased as well.\n",
    "\n",
    "LEARNING_RATE = 0.01\n",
    "LEARNING_RATE_EXP_DECAY = 0.6 if strategy.num_replicas_in_sync == 1 else 0.7\n",
    "# Learning rate computed later as LEARNING_RATE * LEARNING_RATE_EXP_DECAY**epoch\n",
    "# 0.7 decay instead of 0.6 means a slower decay, i.e. a faster learnign rate.\n",
    "\n",
    "training_images_file   = 'gs://mnist-public/train-images-idx3-ubyte'\n",
    "training_labels_file   = 'gs://mnist-public/train-labels-idx1-ubyte'\n",
    "validation_images_file = 'gs://mnist-public/t10k-images-idx3-ubyte'\n",
    "validation_labels_file = 'gs://mnist-public/t10k-labels-idx1-ubyte'"
   ],
   "execution_count": 5,
   "outputs": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Lz1Zknfk4qCx"
   },
   "source": [
    "### tf.data.Dataset: parse files and prepare training and validation datasets\n",
    "Please read the [best practices for building](https://www.tensorflow.org/guide/performance/datasets) input pipelines with tf.data.Dataset"
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "id": "ZE8dgyPC1_6m"
   },
   "source": [
    "def read_label(tf_bytestring):\n",
    "    label = tf.io.decode_raw(tf_bytestring, tf.uint8)\n",
    "    label = tf.reshape(label, [])\n",
    "    label = tf.one_hot(label, 10)\n",
    "    return label\n",
    "  \n",
    "def read_image(tf_bytestring):\n",
    "    image = tf.io.decode_raw(tf_bytestring, tf.uint8)\n",
    "    image = tf.cast(image, tf.float32)/256.0\n",
    "    image = tf.reshape(image, [28*28])\n",
    "    return image\n",
    "  \n",
    "def load_dataset(image_file, label_file):\n",
    "    imagedataset = tf.data.FixedLengthRecordDataset(image_file, 28*28, header_bytes=16)\n",
    "    imagedataset = imagedataset.map(read_image, num_parallel_calls=16)\n",
    "    labelsdataset = tf.data.FixedLengthRecordDataset(label_file, 1, header_bytes=8)\n",
    "    labelsdataset = labelsdataset.map(read_label, num_parallel_calls=16)\n",
    "    dataset = tf.data.Dataset.zip((imagedataset, labelsdataset))\n",
    "    return dataset \n",
    "  \n",
    "def get_training_dataset(image_file, label_file, batch_size):\n",
    "    dataset = load_dataset(image_file, label_file)\n",
    "    dataset = dataset.cache()  # this small dataset can be entirely cached in RAM\n",
    "    dataset = dataset.shuffle(5000, reshuffle_each_iteration=True)\n",
    "    dataset = dataset.repeat()\n",
    "    dataset = dataset.batch(batch_size)\n",
    "    dataset = dataset.prefetch(AUTOTUNE)  # fetch next batches while training on the current one (-1: autotune prefetch buffer size)\n",
    "    return dataset\n",
    "  \n",
    "def get_validation_dataset(image_file, label_file):\n",
    "    dataset = load_dataset(image_file, label_file)\n",
    "    dataset = dataset.cache() # this small dataset can be entirely cached in RAM\n",
    "    dataset = dataset.batch(10000)\n",
    "    return dataset\n",
    "\n",
    "# instantiate the datasets\n",
    "training_dataset = get_training_dataset(training_images_file, training_labels_file, BATCH_SIZE)\n",
    "validation_dataset = get_validation_dataset(validation_images_file, validation_labels_file)"
   ],
   "execution_count": 6,
   "outputs": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "_fXo6GuvL3EB"
   },
   "source": [
    "### Let's have a look at the data"
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 177
    },
    "id": "yZ4tjPKvL2eh",
    "outputId": "0e34e94d-bde3-4c27-8b6d-975aecaf4fdd"
   },
   "source": [
    "N = 24\n",
    "(training_digits, training_labels,\n",
    " validation_digits, validation_labels) = dataset_to_numpy_util(training_dataset, validation_dataset, N)\n",
    "display_digits(training_digits, training_labels, training_labels, \"training digits and their labels\", N)\n",
    "display_digits(validation_digits[:N], validation_labels[:N], validation_labels[:N], \"validation digits and their labels\", N)\n",
    "font_digits, font_labels = create_digits_from_local_fonts(N)"
   ],
   "execution_count": 7,
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 936x216 with 1 Axes>"
      ]
     },
     "metadata": {}
    },
    {
     "output_type": "display_data",
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 936x216 with 1 Axes>"
      ]
     },
     "metadata": {}
    }
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "KIc0oqiD40HC"
   },
   "source": [
    "### Keras model: 3 convolutional layers, 2 dense layers\n",
    "If you are not sure what cross-entropy, dropout, softmax or batch-normalization mean, head here for a crash-course: [Tensorflow and deep learning without a PhD](https://github.com/GoogleCloudPlatform/tensorflow-without-a-phd/#featured-code-sample)"
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "56y8UNFQIVwj",
    "outputId": "e0d1e4a1-94fa-4db6-8b35-9e27f4720ea6"
   },
   "source": [
    "# This model trains to 99.4% accuracy in 10 epochs (with a batch size of 64)  \n",
    "\n",
    "def make_model():\n",
    "    model = tf.keras.Sequential(\n",
    "      [\n",
    "        tf.keras.layers.Reshape(input_shape=(28*28,), target_shape=(28, 28, 1), name=\"image\"),\n",
    "\n",
    "        tf.keras.layers.Conv2D(filters=12, kernel_size=3, padding='same', use_bias=False), # no bias necessary before batch norm\n",
    "        tf.keras.layers.BatchNormalization(scale=False, center=True), # no batch norm scaling necessary before \"relu\"\n",
    "        tf.keras.layers.Activation('relu'), # activation after batch norm\n",
    "\n",
    "        tf.keras.layers.Conv2D(filters=24, kernel_size=6, padding='same', use_bias=False, strides=2),\n",
    "        tf.keras.layers.BatchNormalization(scale=False, center=True),\n",
    "        tf.keras.layers.Activation('relu'),\n",
    "\n",
    "        tf.keras.layers.Conv2D(filters=32, kernel_size=6, padding='same', use_bias=False, strides=2),\n",
    "        tf.keras.layers.BatchNormalization(scale=False, center=True),\n",
    "        tf.keras.layers.Activation('relu'),\n",
    "\n",
    "        tf.keras.layers.Flatten(),\n",
    "        tf.keras.layers.Dense(200, use_bias=False),\n",
    "        tf.keras.layers.BatchNormalization(scale=False, center=True),\n",
    "        tf.keras.layers.Activation('relu'),\n",
    "        tf.keras.layers.Dropout(0.4), # Dropout on dense layer only\n",
    "\n",
    "        tf.keras.layers.Dense(10, activation='softmax')\n",
    "      ])\n",
    "\n",
    "    model.compile(optimizer='adam', # learning rate will be set by LearningRateScheduler\n",
    "                  loss='categorical_crossentropy',\n",
    "                  metrics=['accuracy'])\n",
    "     # Going back and forth between TPU and host is expensive. Better to run 128 batches on the TPU before reporting back.\n",
    "    return model\n",
    "    \n",
    "with strategy.scope():\n",
    "    model = make_model()\n",
    "\n",
    "# print model layers\n",
    "model.summary()\n",
    "\n",
    "# set up learning rate decay\n",
    "lr_decay = tf.keras.callbacks.LearningRateScheduler(\n",
    "    lambda epoch: LEARNING_RATE * LEARNING_RATE_EXP_DECAY**epoch,\n",
    "    verbose=True)"
   ],
   "execution_count": 8,
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "Model: \"sequential\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "image (Reshape)              (None, 28, 28, 1)         0         \n",
      "_________________________________________________________________\n",
      "conv2d (Conv2D)              (None, 28, 28, 12)        108       \n",
      "_________________________________________________________________\n",
      "batch_normalization (BatchNo (None, 28, 28, 12)        36        \n",
      "_________________________________________________________________\n",
      "activation (Activation)      (None, 28, 28, 12)        0         \n",
      "_________________________________________________________________\n",
      "conv2d_1 (Conv2D)            (None, 14, 14, 24)        10368     \n",
      "_________________________________________________________________\n",
      "batch_normalization_1 (Batch (None, 14, 14, 24)        72        \n",
      "_________________________________________________________________\n",
      "activation_1 (Activation)    (None, 14, 14, 24)        0         \n",
      "_________________________________________________________________\n",
      "conv2d_2 (Conv2D)            (None, 7, 7, 32)          27648     \n",
      "_________________________________________________________________\n",
      "batch_normalization_2 (Batch (None, 7, 7, 32)          96        \n",
      "_________________________________________________________________\n",
      "activation_2 (Activation)    (None, 7, 7, 32)          0         \n",
      "_________________________________________________________________\n",
      "flatten (Flatten)            (None, 1568)              0         \n",
      "_________________________________________________________________\n",
      "dense (Dense)                (None, 200)               313600    \n",
      "_________________________________________________________________\n",
      "batch_normalization_3 (Batch (None, 200)               600       \n",
      "_________________________________________________________________\n",
      "activation_3 (Activation)    (None, 200)               0         \n",
      "_________________________________________________________________\n",
      "dropout (Dropout)            (None, 200)               0         \n",
      "_________________________________________________________________\n",
      "dense_1 (Dense)              (None, 10)                2010      \n",
      "=================================================================\n",
      "Total params: 354,538\n",
      "Trainable params: 354,002\n",
      "Non-trainable params: 536\n",
      "_________________________________________________________________\n"
     ]
    }
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "CuhDh8ao8VyB"
   },
   "source": [
    "### Train and validate the model"
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "TTwH_P-ZJ_xx",
    "outputId": "9b18bcc5-7816-4602-d36d-52dae581d13a"
   },
   "source": [
    "EPOCHS = 10\n",
    "steps_per_epoch = 60000//BATCH_SIZE  # 60,000 items in this dataset\n",
    "print(\"Steps per epoch: \", steps_per_epoch)\n",
    "  \n",
    "history = model.fit(training_dataset,\n",
    "                    steps_per_epoch=steps_per_epoch, epochs=EPOCHS,\n",
    "                    validation_data=validation_dataset, validation_steps=1,\n",
    "                    callbacks=[lr_decay])"
   ],
   "execution_count": 9,
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "Steps per epoch:  117\n",
      "Epoch 1/10\n",
      "\n",
      "Epoch 00001: LearningRateScheduler setting learning rate to 0.01.\n",
      "117/117 [==============================] - 10s 39ms/step - loss: 0.1678 - accuracy: 0.9493 - val_loss: 3.1334 - val_accuracy: 0.1425\n",
      "Epoch 2/10\n",
      "\n",
      "Epoch 00002: LearningRateScheduler setting learning rate to 0.006999999999999999.\n",
      "117/117 [==============================] - 2s 18ms/step - loss: 0.0516 - accuracy: 0.9843 - val_loss: 3.3389 - val_accuracy: 0.1972\n",
      "Epoch 3/10\n",
      "\n",
      "Epoch 00003: LearningRateScheduler setting learning rate to 0.0049.\n",
      "117/117 [==============================] - 2s 18ms/step - loss: 0.0322 - accuracy: 0.9899 - val_loss: 0.6359 - val_accuracy: 0.7760\n",
      "Epoch 4/10\n",
      "\n",
      "Epoch 00004: LearningRateScheduler setting learning rate to 0.003429999999999999.\n",
      "117/117 [==============================] - 2s 17ms/step - loss: 0.0236 - accuracy: 0.9924 - val_loss: 0.0654 - val_accuracy: 0.9786\n",
      "Epoch 5/10\n",
      "\n",
      "Epoch 00005: LearningRateScheduler setting learning rate to 0.0024009999999999995.\n",
      "117/117 [==============================] - 2s 17ms/step - loss: 0.0170 - accuracy: 0.9949 - val_loss: 0.0428 - val_accuracy: 0.9870\n",
      "Epoch 6/10\n",
      "\n",
      "Epoch 00006: LearningRateScheduler setting learning rate to 0.0016806999999999994.\n",
      "117/117 [==============================] - 2s 18ms/step - loss: 0.0122 - accuracy: 0.9965 - val_loss: 0.0261 - val_accuracy: 0.9920\n",
      "Epoch 7/10\n",
      "\n",
      "Epoch 00007: LearningRateScheduler setting learning rate to 0.0011764899999999997.\n",
      "117/117 [==============================] - 2s 18ms/step - loss: 0.0099 - accuracy: 0.9973 - val_loss: 0.0194 - val_accuracy: 0.9937\n",
      "Epoch 8/10\n",
      "\n",
      "Epoch 00008: LearningRateScheduler setting learning rate to 0.0008235429999999996.\n",
      "117/117 [==============================] - 2s 18ms/step - loss: 0.0084 - accuracy: 0.9977 - val_loss: 0.0209 - val_accuracy: 0.9929\n",
      "Epoch 9/10\n",
      "\n",
      "Epoch 00009: LearningRateScheduler setting learning rate to 0.0005764800999999997.\n",
      "117/117 [==============================] - 2s 18ms/step - loss: 0.0074 - accuracy: 0.9982 - val_loss: 0.0191 - val_accuracy: 0.9939\n",
      "Epoch 10/10\n",
      "\n",
      "Epoch 00010: LearningRateScheduler setting learning rate to 0.0004035360699999998.\n",
      "117/117 [==============================] - 2s 18ms/step - loss: 0.0063 - accuracy: 0.9984 - val_loss: 0.0195 - val_accuracy: 0.9937\n"
     ]
    }
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "9jFVovcUUVs1"
   },
   "source": [
    "### Visualize predictions"
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 561
    },
    "id": "w12OId8Mz7dF",
    "outputId": "bb4b80d0-d2ae-4e61-d0e2-faa609a0360f"
   },
   "source": [
    "# recognize digits from local fonts\n",
    "probabilities = model.predict(font_digits, steps=1)\n",
    "predicted_labels = np.argmax(probabilities, axis=1)\n",
    "display_digits(font_digits, predicted_labels, font_labels, \"predictions from local fonts (bad predictions in red)\", N)\n",
    "\n",
    "# recognize validation digits\n",
    "probabilities = model.predict(validation_digits, steps=1)\n",
    "predicted_labels = np.argmax(probabilities, axis=1)\n",
    "display_top_unrecognized(validation_digits, predicted_labels, validation_labels, N, 7)"
   ],
   "execution_count": 10,
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 936x216 with 1 Axes>"
      ]
     },
     "metadata": {}
    },
    {
     "output_type": "display_data",
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 936x216 with 1 Axes>"
      ]
     },
     "metadata": {}
    },
    {
     "output_type": "display_data",
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 936x216 with 1 Axes>"
      ]
     },
     "metadata": {}
    },
    {
     "output_type": "display_data",
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 936x216 with 1 Axes>"
      ]
     },
     "metadata": {}
    },
    {
     "output_type": "display_data",
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 936x216 with 1 Axes>"
      ]
     },
     "metadata": {}
    },
    {
     "output_type": "display_data",
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 936x216 with 1 Axes>"
      ]
     },
     "metadata": {}
    },
    {
     "output_type": "display_data",
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 936x216 with 1 Axes>"
      ]
     },
     "metadata": {}
    },
    {
     "output_type": "display_data",
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 936x216 with 1 Axes>"
      ]
     },
     "metadata": {}
    }
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "5tzVi39ShrEL"
   },
   "source": [
    "## Deploy the trained model to AI Platform prediction\n",
    "\n",
    "Push your trained model to production on AI Platform for a serverless, autoscaled, REST API experience.\n",
    "\n",
    "You will need a GCS (Google Cloud Storage) bucket and a GCP project for this.\n",
    "Models deployed on AI Platform autoscale to zero if not used. There will be no AI Platform charges after you are done testing.\n",
    "Google Cloud Storage incurs charges. Empty the bucket after deployment if you want to avoid these. Once the model is deployed, the bucket is not useful anymore."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "3Y3ztMY_toCP"
   },
   "source": [
    "### Configuration"
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "id": "iAZAn7yIhqAS"
   },
   "source": [
    "PROJECT = \"\" #@param {type:\"string\"}\n",
    "BUCKET = \"gs://\"  #@param {type:\"string\", default:\"jddj\"}\n",
    "NEW_MODEL = True #@param {type:\"boolean\"}\n",
    "MODEL_NAME = \"mnist\" #@param {type:\"string\"}\n",
    "MODEL_VERSION = \"v1\" #@param {type:\"string\"}\n",
    "\n",
    "assert PROJECT, 'For this part, you need a GCP project. Head to http://console.cloud.google.com/ and create one.'\n",
    "assert re.search(r'gs://.+', BUCKET), 'For this part, you need a GCS bucket. Head to http://console.cloud.google.com/storage and create one.'"
   ],
   "execution_count": null,
   "outputs": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Lzd6Qi464PsA"
   },
   "source": [
    "### Colab-only auth"
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "cellView": "both",
    "id": "MPx0nvyUnvgT"
   },
   "source": [
    "IS_COLAB_BACKEND = 'COLAB_GPU' in os.environ  # this is always set on Colab, the value is 0 or 1 depending on GPU presence\n",
    "if IS_COLAB_BACKEND:\n",
    "  from google.colab import auth\n",
    "  auth.authenticate_user() # Authenticates the Colab machine to access your private GCS buckets."
   ],
   "execution_count": null,
   "outputs": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "GxQTtjmdIbmN"
   },
   "source": [
    "### Export the model for serving from AI Platform"
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "id": "GOgh7Kb7SzzG"
   },
   "source": [
    "export_path = os.path.join(BUCKET, 'keras_export', str(time.time()))\n",
    "\n",
    "# The serving function performig data pre- and post-processing.\n",
    "# The model itself is captured  by this function by closure.\n",
    "# Pre-processing:  images are received in uint8 format converted\n",
    "#                  to float32 before being sent to through the model.\n",
    "# Post-processing: the Keras model outputs digit probabilities. We want\n",
    "#                  the detected digits. An additional tf.argmax is needed.\n",
    "# @tf.function turns the code in this function into a Tensorflow graph that\n",
    "# can be exported. This way, the model itself, as well as its pre- and post-\n",
    "# processing steps are exported in the SavedModel and deployed in a single step.\n",
    "@tf.function(input_signature=[tf.TensorSpec([None, 28*28], dtype=tf.uint8)])\n",
    "def my_serve(images):\n",
    "  images = tf.cast(images, tf.float32)/255   # pre-processing\n",
    "  probabilities = model(images, training=False) # prediction from model (inference graph only)\n",
    "  classes = tf.argmax(probabilities, axis=-1) # post-processing\n",
    "  return {'digits': classes}\n",
    "\n",
    "# exporting in the Tensorflow standard SavedModel format with a serving input function\n",
    "model.save(export_path, signatures={'serving_default': my_serve}, save_format=\"tf\")\n",
    "print(\"Model exported to: \", export_path)"
   ],
   "execution_count": null,
   "outputs": []
  },
  {
   "cell_type": "code",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 289
    },
    "id": "Zm7cpCRQC8-w",
    "outputId": "b4d9c5c5-67e5-4bec-f6a6-ff4c192227f9"
   },
   "source": [
    "# saved_model_cli: a useful too for troubleshooting SavedModels (the tool is part of the Tensorflow installation)\n",
    "!saved_model_cli show --dir {export_path}\n",
    "!saved_model_cli show --dir {export_path} --tag_set serve\n",
    "!saved_model_cli show --dir {export_path} --tag_set serve --signature_def serving_default\n",
    "# A note on naming:\n",
    "# The \"serve\" tag set (i.e. serving functionality) is the only one exported by tf.saved_model.save\n",
    "# All the other names are defined by the user in the fllowing lines of code:\n",
    "#      def myserve(self, images):\n",
    "#                        ******\n",
    "#        return {'digits': classes}\n",
    "#                 ******\n",
    "#      tf.saved_model.save(..., signatures={'serving_default': serving_model.myserve})\n",
    "#                                            ***************"
   ],
   "execution_count": null,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The given SavedModel contains the following tag-sets:\n",
      "serve\n",
      "The given SavedModel MetaGraphDef contains SignatureDefs with the following keys:\n",
      "SignatureDef key: \"__saved_model_init_op\"\n",
      "SignatureDef key: \"serving_default\"\n",
      "The given SavedModel SignatureDef contains the following input(s):\n",
      "  inputs['images'] tensor_info:\n",
      "      dtype: DT_UINT8\n",
      "      shape: (-1, 784)\n",
      "      name: serving_default_images:0\n",
      "The given SavedModel SignatureDef contains the following output(s):\n",
      "  outputs['digits'] tensor_info:\n",
      "      dtype: DT_INT64\n",
      "      shape: (-1)\n",
      "      name: StatefulPartitionedCall:0\n",
      "Method name is: tensorflow/serving/predict\n"
     ]
    }
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "zy3T3zk0u2J0"
   },
   "source": [
    "### Deploy the model\n",
    "This uses the command-line interface. You can do the same thing through the AI Platform UI at https://console.cloud.google.com/ai-platform/models\n"
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "id": "nGv3ITiGLPL3"
   },
   "source": [
    "# Create the model\n",
    "if NEW_MODEL:\n",
    "  !gcloud ai-platform models create {MODEL_NAME} --project={PROJECT} --regions=us-central1"
   ],
   "execution_count": null,
   "outputs": []
  },
  {
   "cell_type": "code",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 51
    },
    "id": "o3QtUowtOAL-",
    "outputId": "53c0586a-3364-4e5b-fa4d-5b486c83d535"
   },
   "source": [
    "# Create a version of this model (you can add --async at the end of the line to make this call non blocking)\n",
    "# Additional config flags are available: https://cloud.google.com/ai-platform/prediction/docs/reference/rest/v1/projects.models.versions\n",
    "!echo \"Deployment takes a couple of minutes. You can watch your deployment here: https://console.cloud.google.com/ai-platform/models/{MODEL_NAME}\"\n",
    "!gcloud ai-platform versions create {MODEL_VERSION} --model={MODEL_NAME} --origin={export_path} --project={PROJECT} --runtime-version=2.1 --python-version=3.7"
   ],
   "execution_count": null,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Deployment takes a couple of minutes. You can watch your deployment here: https://console.cloud.google.com/ai-platform/models/mnist\n",
      "\u001B[1;33mWARNING:\u001B[0m Using endpoint [https://ml.googleapis.com/]\n"
     ]
    }
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "jE-k1Zn6kU2Z"
   },
   "source": [
    "### Test the deployed model\n",
    "Your model is now available as a REST API. Let us try to call it. The cells below use the \"gcloud ai-platform\"\n",
    "command line tool but any tool that can send a JSON payload to a REST endpoint will work."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "id": "zZCt0Ke2QDer"
   },
   "source": [
    "# prepare digits to send to online prediction endpoint\n",
    "digits_float32 = np.concatenate((font_digits, validation_digits[:100-N])) # pixel values in [0.0, 1.0] float range\n",
    "digits_uint8 = np.round(digits_float32*255).astype(np.uint8) # pixel values in [0, 255] int range\n",
    "labels = np.concatenate((font_labels, validation_labels[:100-N]))\n",
    "with open(\"digits.json\", \"w\") as f:\n",
    "  for digit in digits_uint8:\n",
    "    # the format for AI Platform online predictions is: one JSON object per line\n",
    "    data = json.dumps({\"images\": digit.tolist()})  # \"images\" because that was the name you gave this parametr in the serving funtion my_serve\n",
    "    f.write(data+'\\n')"
   ],
   "execution_count": null,
   "outputs": []
  },
  {
   "cell_type": "code",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 326
    },
    "id": "n6PqhQ8RQ8bp",
    "outputId": "edbca3a8-963d-494d-9501-ba8ad0ce562d"
   },
   "source": [
    "# Request online predictions from deployed model (REST API) using the \"gcloud ml-engine\" command line.\n",
    "predictions = !gcloud ai-platform predict --model={MODEL_NAME} --json-instances digits.json --project={PROJECT} --version {MODEL_VERSION}\n",
    "print(predictions)\n",
    "\n",
    "predictions = np.array([int(p) for p in predictions if p.isdigit()])\n",
    "display_top_unrecognized(digits_float32, predictions, labels, N, 100//N)"
   ],
   "execution_count": null,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['\\x1b[1;33mWARNING:\\x1b[0m Using endpoint [https://ml.googleapis.com/]', 'DIGITS', '0', '1', '2', '3', '4', '5', '6', '7', '8', '9', '0', '1', '2', '3', '4', '5', '6', '7', '8', '9', '0', '1', '2', '3', '7', '2', '1', '0', '4', '1', '4', '9', '5', '9', '0', '6', '9', '0', '1', '5', '9', '7', '3', '4', '9', '6', '6', '5', '4', '0', '7', '4', '0', '1', '3', '1', '3', '4', '7', '2', '7', '1', '2', '1', '1', '7', '4', '2', '3', '5', '1', '2', '4', '4', '6', '3', '5', '5', '6', '0', '4', '1', '9', '5', '7', '8', '9', '3', '7', '4', '6', '4', '3', '0', '7', '0', '2', '9', '1', '7']\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 936x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 936x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 936x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 936x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "tags": []
     },
     "output_type": "display_data"
    }
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "SVY1pBg5ydH-"
   },
   "source": [
    "## License"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "hleIN5-pcr0N"
   },
   "source": [
    "\n",
    "\n",
    "---\n",
    "\n",
    "\n",
    "author: Martin Gorner<br>\n",
    "twitter: @martin_gorner\n",
    "\n",
    "\n",
    "---\n",
    "\n",
    "\n",
    "Copyright 2021 Google LLC\n",
    "\n",
    "Licensed under the Apache License, Version 2.0 (the \"License\");\n",
    "you may not use this file except in compliance with the License.\n",
    "You may obtain a copy of the License at\n",
    "\n",
    "    http://www.apache.org/licenses/LICENSE-2.0\n",
    "\n",
    "Unless required by applicable law or agreed to in writing, software\n",
    "distributed under the License is distributed on an \"AS IS\" BASIS,\n",
    "WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
    "See the License for the specific language governing permissions and\n",
    "limitations under the License.\n",
    "\n",
    "\n",
    "---\n",
    "\n",
    "\n",
    "This is not an official Google product but sample code provided for an educational purpose\n"
   ]
  }
 ]
}